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Journal articles on the topic 'Estimation of agricultural produce'

Author: Grafiati

Published: 3 June 2025

Last updated: 1 August 2025

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1

John Onuwa, Okoh, and Sunday Nwakwanogo. "Exchange Rate Volatility and Export of Agricultural Produce in Nigeria." International Journal of Development and Economic Sustainability 12, no. 2 (2024): 70–87. http://dx.doi.org/10.37745/ijdes.13/vol12n27087.

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This study examined the effect of exchange rate variation on the export of agricultural produce in Nigeria. The specific objectives of the study include; examining the effects of exchange rate variation; Trade openness; Agricultural financing; and Agricultural employment on the export of agricultural produce in Nigeria. This study adopted the VAR estimation technique in ascertaining the nexus between exchange rate variation and the export of agricultural produce in Nigeria. Data for this study were sourced from World Development Indicators, WDI, a publication of the World Bank; Central Bank of

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2

Singh, Dharmendra Kumar, Shivam, Vikas Kumar Singh, Vijay Kumar Singh, Manish Kumar, and Pramod Kumar Mishra. "Agricultural Water Footprint Studies for Sustainable Agricultural Water Management -A Review." International Journal of Environment and Climate Change 13, no. 9 (2023): 238–50. http://dx.doi.org/10.9734/ijecc/2023/v13i92259.

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Water footprint is defined as the amount of water consumed in production of any agricultural or industrial produce. It accounts the water consumed directly and indirectly for producing any industrial and agricultural product. Water footprint analysis helps in planning of the optimum utilization of water in any sector which subsequently leads to sustainable management of water resources. This review paper provides a review on the Water Footprint estimation methodology its merit and shortcomings, practical challenges with available data and resources for Indian context and worldwide. With increa

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3

Young, Linda J., and Lu Chen. "Using Small Area Estimation to Produce Official Statistics." Stats 5, no. 3 (2022): 881–97. http://dx.doi.org/10.3390/stats5030051.

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The USDA National Agricultural Statistics Service (NASS) and other federal statistical agencies have used probability-based surveys as the foundation for official statistics for over half a century. Non-survey data that can be used to improve the accuracy and precision of estimates such as administrative, remotely sensed, and retail data have become increasingly available. Both frequentist and Bayesian models are used to combine survey and non-survey data in a principled manner. NASS has recently adopted Bayesian subarea models for three of its national programs: farm labor, crop county estima

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Falchenko, Olena, and Oleksandr Volobuev. "FEATURES OF CLASSIFICATION OF PROFITS OF AGRICULTURAL ENTERPRISE." Bulletin of the National Technical University "Kharkiv Polytechnic Institute" (economic sciences), no. 3 (August 26, 2021): 68–71. http://dx.doi.org/10.20998/2519-4461.2021.3.68.

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In the article the description of agricultural enterprise and features of agriculture are given. It is consist in by main and specific capital goods. The profits of agricultural enterprise as economic category are considered, which represent the optimal return of enterprises generating in sizes, necessary for coverage of him current outlays. General essence of profits of agricultural activity, confession of profit is analysed and his reliable estimation. Principles, which foresee the choice of method of estimation and reflection in the financial reporting of all profits of enterprise, and also

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Yahia, Oualid, Raffaella Guida, and Pasquale Iervolino. "Novel Weight-Based Approach for Soil Moisture Content Estimation via Synthetic Aperture Radar, Multispectral and Thermal Infrared Data Fusion." Sensors 21, no. 10 (2021): 3457. http://dx.doi.org/10.3390/s21103457.

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Though current remote sensing technologies, especially synthetic aperture radars (SARs), exhibit huge potential for soil moisture content (SMC) retrievals, such technologies also present several performance disadvantages. This study explored the merits of proposing a novel data fusion methodology (partly decision level and partly feature level) for SMC estimation. Initially, individual estimations were derived from three distinct methods: the inversion of an Empirically Adapted Integral Equation Model (EA-IEM) applied to SAR data, the Perpendicular Drought Index (PDI), and the Temperature Vege

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6

Gil, Antonio, and M. Beltran Siñani. "FEASIBILITY TO PRODUCING SECOND GENERATION BIOETHANOL IN BOLIVIA." Latin American Applied Research - An international journal 51, no. 1 (2020): 57–61. http://dx.doi.org/10.52292/j.laar.2021.541.

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The bioethanol that is produced worldwide is mostly obtained from agricultural crops such as sugarcane and corn. However, it has negative environmental effects, so the option of producing bioethanol from agricultural waste arises. This work evaluates the feasibility to produce second generation bietanol from oranges residues (peel and bagasse) produced in the province of Chapare, Bolivia. The estimation is carried out from the reducing sugars, determined by the DNS method, individual sugars, determined by HPLC, produced by acidic and enzymatic hydrolysis of the residues. Similarly, the amount

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7

Dudung, D., B. Abbas, E. A. Martanto, et al. "Estimation of greenhouse gases in rice fields and plantations in Teluk Bintuni Regency, West Papua." IOP Conference Series: Earth and Environmental Science 1192, no. 1 (2023): 012012. http://dx.doi.org/10.1088/1755-1315/1192/1/012012.

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Abstract The study purpose was to estimate greenhouse gases produced in agricultural sector in Teluk Bintuni Regency. Data were taken from 15 farmer groups from 15 districts, and 6 families of rice farmers assisted by Tangguh LNG’ CSR. The calculation method uses IPCC 2006 Tier 2. The correction factor used in calculating Bintuni’s GHG is adjusted based on land area, soil type, type of fertilizer, and type of irrigation used. The results show that paddy farming activities by rice farmers assisted by Tangguh LNG CSR produce CH4 of 964.45 kg/year, or CO2 of 20.253,54 kg/year. Fertilization activ

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Yang, Yanqing, Zhenxin Bao, Houfa Wu, et al. "An Exponential Filter Model-Based Root-Zone Soil Moisture Estimation Methodology from Multiple Datasets." Remote Sensing 14, no. 8 (2022): 1785. http://dx.doi.org/10.3390/rs14081785.

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Modern smart agriculture initiative presents more requests for soil moisture (SM) monitoring over large agricultural areas. Remote sensing techniques facilitate high-resolution surface SM (SSM) estimation at a large scale but lack root zone SM (RZSM) information. Establishing the deduction method of RZSM from the SSM has long been the focus of most attention. Data assimilation methods are promising techniques for RZSM estimation, developing numerous assimilated reanalysis datasets, e.g., ERA5 and the latest Soil Moisture Active and Passive (SMAP) L4 SM product. However, data latency and large

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9

Gonzalez Cruz, Marangely, E. Annette Hernandez, and Venkatesh Uddameri. "Climatic Influences on Agricultural Drought Risks Using Semiparametric Kernel Density Estimation." Water 12, no. 10 (2020): 2813. http://dx.doi.org/10.3390/w12102813.

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A bivariate kernel density estimation (KDE) method was utilized to develop a stochastic framework to assess how agricultural droughts are related to unfavorable meteorological conditions. KDE allows direct estimation of the bivariate cumulative density function which can be used to extract the marginal distributions with minimal subjectivity. The approach provided excellent fits to bivariate relationships between the standardized soil moisture index (SSMI) computed at three- and six-month accumulations and standardized measures of precipitation (P), potential evapotranspiration (PET), and atmo

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Ogunleye, Olusogo, Akinyemi Ajibola, Oluwafemi Enilolobo, and Olufolakemi Shogunle. "Influence of road transport infrastructure on agricultural sector development in Nigeria." Logistics & Sustainable Transport 9, no. 1 (2018): 39–50. http://dx.doi.org/10.2478/jlst-2018-0004.

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AbstractThe study investigated the effects of road transport infrastructure on agricultural sector development in Nigeria from 1985 to 2014, using secondary annual time series data on agricultural development (proxy by gross domestic product in the Agric sector) road transport infrastructure (proxy by length of paved road per square kilometer of area) export and capital, all obtained from the Central Bank of Nigeria (CBN) [3], and National Bureau of Statistics (NBS) [16], statistical bulletins. The data were analyzed using Granger Causality test and Ordinary Least Square estimation techniques.

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Liu, Jiandong, Jun Du, Fei Wang, et al. "Optimal Methods for Estimating Shortwave and Longwave Radiation to Accurately Calculate Reference Crop Evapotranspiration in the High-Altitude of Central Tibet." Agronomy 14, no. 10 (2024): 2401. http://dx.doi.org/10.3390/agronomy14102401.

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The FAO56 Penman–Monteith model (FAO56-PM) is widely used for estimating reference crop evapotranspiration (ET0). However, key variables such as shortwave radiation (Rs) and net longwave radiation (Rln) are often unavailable at most weather stations. While previous studies have focused on calibrating Rs, the influence of large Rln, particularly in high-altitude regions with thin air, remains unexplored. This study investigates this issue by using observed data from Bange in central Tibet to identify the optimal methods for estimating Rs and Rln to accurately calculate ET0. The findings reveal

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Zhu, Hong Jun. "Value Engineering-Oriented Approach to Evaluating Conceptual Design Schemes of Sugarcane Harvester." Advanced Materials Research 468-471 (February 2012): 1300–1307. http://dx.doi.org/10.4028/www.scientific.net/amr.468-471.1300.

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In order to improve agricultural machinery product value in conceptual design scheme evaluation, a novel approach was put forward to evaluate conceptual design schemes in the view of value engineering. Realization of the method was divided into cost estimation and function evaluation. In cost estimation, weighted mahalanobis distance between historical data and estimating product schemes were calculated to express their similarity, their cost attributes were described by different membership functions, exponential smoothing method was selected to get estimation solution; in function evaluation

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13

Xie, Fangzheng, and Yanxun Xu. "Optimal Bayesian estimation for random dot product graphs." Biometrika 107, no. 4 (2020): 875–89. http://dx.doi.org/10.1093/biomet/asaa031.

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Summary We propose and prove the optimality of a Bayesian approach for estimating the latent positions in random dot product graphs, which we call posterior spectral embedding. Unlike classical spectral-based adjacency, or Laplacian spectral embedding, posterior spectral embedding is a fully likelihood-based graph estimation method that takes advantage of the Bernoulli likelihood information of the observed adjacency matrix. We develop a minimax lower bound for estimating the latent positions, and show that posterior spectral embedding achieves this lower bound in the following two senses: it

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Agusta, Madania Tetiani, Bagus Sartono, and Anik Djuraidah. "Evaluation of Spatial Approaches of Poverty in East Java." Journal of Mathematics, Computations and Statistics 8, no. 1 (2025): 187–98. https://doi.org/10.35580/jmathcos.v8i1.7663.

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Geographically Weighted Regression (GWR) is the most frequently used for spatial modeling. GWR produces local model parameter estimates for each observed point. Unfortunately, GWR is known to be numerically unstable and can produce extreme coefficient estimates. Spatially Clustered Regression (SCR) and Spatially Constrained Clusterwise Regression (SCCR) are new approaches that combine cluster identification and regression estimation in one stage. This research evaluates these approaches to develop poverty alleviation in East Java with the largest number of poor people in rural areas as per Mar

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15

Banasik, K., and D. E. Walling. "Predicting Sedimentgraphs for a Small Agricultural Catchment." Hydrology Research 27, no. 4 (1996): 275–94. http://dx.doi.org/10.2166/nh.1996.0010.

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The key components of a sedimentgraph prediction procedure for small agricultural catchments are outlined in the paper. An instantaneous unit sedimentgraph (IUSG) based on the IUH and on a dimensionless sediment concentration distribution is developed, and used for transforming the sediment produced during a specified rainfall duration into a sedimentgraph. Rainfall-runoff-suspended sediment transport data from the River Dart basin, in Devon, UK, are used to evaluate several relationships for sediment yield estimation. The relationship between the lag time of the direct runoff hydrograph and t

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16

Ogundeji, Abiodun, Andre Jooste, and D. Uchezuba. "Econometric estimation of Armington elasticities for selected agricultural products in South Africa." South African Journal of Economic and Management Sciences 13, no. 2 (2010): 123–34. http://dx.doi.org/10.4102/sajems.v13i2.41.

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Price transmission behaviour is used to model the impacts of different trade regimes; if this behaviour is not modelled correctly, the trade impacts can be either under- or overestimated. Due to the lack of elasticities of substitution pertaining to selected imported and domestically produced agricultural products in South Africa, ‘Armington’ elasticities, using quarterly data from 1995-2006 and three different models, based on the time series properties of the data, are estimated in this paper. Considering the long-run elasticity results, soyabeans (whether broken or not) and meat of bovine a

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17

De Miguel, Ángel, Eloy García, and Irene De Buestamante. "Estimation of the virtual water trade between two Spanish regions: Castilla-la Mancha and Murcia." Water Supply 10, no. 5 (2010): 831–40. http://dx.doi.org/10.2166/ws.2010.477.

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Virtual water is defined as the water needed to produce a product. We can use virtual water flow calculations to estimate the water efficiency of a country, as well as its economic dependence on water resources. Former studies on this area have focused on quantifying the virtual water flows between countries, in an international context. In this study we reduce the action framework to regions within a country, determining the virtual water balance between two Spanish regions: Castilla-La Mancha and Murcia. In 2004, Castilla-La Mancha exported to Murcia 2,453,442 tons of commercial products, fr

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18

Erciulescu, Andreea L., Nathan B. Cruze, and Balgobin Nandram. "Statistical Challenges in Combining Survey and Auxiliary Data to Produce Official Statistics." Journal of Official Statistics 36, no. 1 (2020): 63–88. http://dx.doi.org/10.2478/jos-2020-0004.

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AbstractCombining survey and auxiliary data to produce official statistics is gaining interest at federal agencies and among policy makers due to its efficiency. Recent studies have shown the practicality of small area estimation modeling approaches in the context of integrating data from multiple sources to improve estimation at fine levels of aggregation. In this article, agricultural predictions are constructed using a hierarchical Bayes subarea-level model, fit to data available from different sources. Auxiliary data are initially used to complement the survey data and define the predictio

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19

Havelaar, Arie H., Kathleen M. Vazquez, Zeynal Topalcengiz, Rafael Muñoz-Carpena, and MICHELLE D. DANYLUK. "Evaluating the U.S. Food Safety Modernization Act Produce Safety Rule Standard for Microbial Quality of Agricultural Water for Growing Produce." Journal of Food Protection 80, no. 11 (2017): 1832–41. http://dx.doi.org/10.4315/0362-028x.jfp-17-122.

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ABSTRACT The U.S. Food and Drug Administration (FDA) has defined standards for the microbial quality of agricultural surface water used for irrigation. According to the FDA produce safety rule (PSR), a microbial water quality profile requires analysis of a minimum of 20 samples for Escherichia coli over 2 to 4 years. The geometric mean (GM) level of E. coli should not exceed 126 CFU/100 mL, and the statistical threshold value (STV) should not exceed 410 CFU/100 mL. The water quality profile should be updated by analysis of a minimum of five samples per year. We used an extensive set of data on

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20

KURITA, Mitsutaka, and Naoshi KONDO. "Agricultural Product Grading Method by Image Processing (Part 2) -Agricultural Product Mass Estimation Experiment by Color CCD Cameras-." Shokubutsu Kankyo Kogaku 18, no. 1 (2006): 18–27. http://dx.doi.org/10.2525/shita.18.18.

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21

Walker, Elisabet, and Virginia Venturini. "Improving the evapotranspiration estimation by coupling soil moisture and atmospheric variables in the relative evapotranspiration parameterization." Revista de Teledetección, no. 63 (January 30, 2024): 65–77. http://dx.doi.org/10.4995/raet.2024.20158.

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Accurate monthly evapotranspiration (ET) estimation is essential for many forest, climate, and hydrological applications, as well as for some agricultural uses. In this study, the relationship between ET and relative evapotranspiration (F) using land surface, and atmospheric variables was assessed with 17 FLUXNET sites data in savanna, cropland, and forest land covers, distributed all over the world. A sigmoid (Fs) and a logarithmic (Fl) F expression were included in Walker et al.’s (2019a,b) equations to evaluate their impact on the accuracy of ET estimations. The new parameterizations of ET

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22

Falchenko, Olena, Viktoriia Yatsyna, and Tetyana Kochetova. "A FEATURES OF FORMING OF FINANCIAL RESULTS OF AGRICULTURAL ENTERPRISE." Bulletin of the National Technical University "Kharkiv Polytechnic Institute" (economic sciences), no. 2 (April 12, 2021): 32–36. http://dx.doi.org/10.20998/2519-4461.2021.2.32.

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In the article essence over of agricultural enterprises is brought after the type of economic activity as a legal entity, the basic type of activity of which is growing and processing of agricultural produce and specific of agriculture, as to the type of economic activity. The financial results of agricultural enterprises as economic category which represents effectiveness of activity of agricultural enterprise are considered. General methodology of determination of financial results of agricultural activity is analysed on accordance to the real model of market economy. The existent substantia

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Chen, Yonghong. "Estimage: A mobile application in agriculture for image to object count estimation." Proceedings of the Nova Scotian Institute of Science (NSIS) 49, no. 1 (2017): 119. http://dx.doi.org/10.15273/pnsis.v49i1.6983.

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A major problem in the agricultural field is accurately estimating the yield of produce. Typically, farmers must wait to measure their crops after harvest using manual mechanical equipment. There is value in having better methods of yield estimation based on data that can be captured with inexpensive technology in the field, such as a smartphone. We develop a smartphone application for the Android platform with access to a cloud-based machine learning (ML) service that can estimate the amount of crop on a bush or tree from an image. The development of an image-to-object-count estimation system

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Okunlola, Funso Abiodun, Godswill Osagie Osuma, and Ehimare Alexander Omankhanlen. "AGRICULTURAL FINANCE AND ECONOMIC GROWTH: EVIDENCE FROM NIGERIA." Business: Theory and Practice 20 (November 28, 2019): 467–75. http://dx.doi.org/10.3846/btp.2019.43.

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The study performed an in-depth examination of the impact of guaranteed agricultural finance to oil palm, cocoa, groundnuts, fishery, poultry, cattle, roots, and tubers on the real gross domestic product of the country. Time series data was sourced from the Central Bank of Nigeria statistical bulletin of various issues. The data sets covered thirty-seven (37) years spanning from 1981 to 2017. The study used Autoregressive Distributed Lag (ARDL) model for its analysis. However, prior estimation and due to several exogenous variables, Phillip Perron stationarity test was used to determine the or

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Aguirre González, Medardo, Claudio Candia Campano, and Lilliam Antón López. "A Gravity Model of Trade for Nicaraguan Agricultural Exports." Cuadernos de Economía 37, no. 74 (2018): 391–428. http://dx.doi.org/10.15446/cuad.econ.v37n74.55016.

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This research aims to find the determining factors of Nicaraguan agricultural exports. To carry out this study, the author formulated a Gravity Model of Trade (GMT) and then made an estimation using a version of Ordinary Least Squares (OLS) that incorporates a consistent covariance matrix estimator to correct the heteroskedasticity and autocorrelation effects. The data considered observations over twenty years and for twelve countries: eight have signed a Free Trade Agreement (FTA) with Nicaragua and four have not. The variables that significantly increased the flow of Nicaraguan agricultural

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Aboyitungiye, J. B., and D. Prasetyani. "Is agriculture an engine of economic reconstruction and development in the case of the Republic of Burundi?" IOP Conference Series: Earth and Environmental Science 905, no. 1 (2021): 012071. http://dx.doi.org/10.1088/1755-1315/905/1/012071.

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Abstract Despite its importance for the economy, the agricultural sector faces many constraints that hamper its growth. With the increase in the world population and the demand for food production, farmers need to produce more with less arable land. This study used the ARDL approach to model the long-term and short-term dynamics and proposed examining the agricultural sector’s contribution to Burundi’s economic growth. Econometric estimations revealed that the gross domestic product per capita, agricultural, and exports (value-added) have long-run relationships but at different levels. The stu

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Frem, Michel, Alessandro Petrontino, Vincenzo Fucilli, Carlo Sansiviero, and Francesco Bozzo. "Sustainable Viticulture of Italian Grapevines: Environmental Evaluation and Societal Cost Estimation Using EU Farm Accountancy Data Network Data." Horticulturae 9, no. 11 (2023): 1239. http://dx.doi.org/10.3390/horticulturae9111239.

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Since the agriculture sector, such as Italian grapevine production, exert a pressure on the environment to some extent, this research aims to evaluate the environmental impacts and estimate the societal costs of four current grapevine production systems (i.e., vine grapes cultivated to produce common or quality wine using organic and non-organic agricultural practices), based on the Italian Farm Accountancy Network Data. For these purposes, the Life Cycle Analysis and Shadow Price techniques have been used. The results revealed that the levels of environmental impacts differed considerably bet

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Ferri, Clotilde Pinheiro, Antonio Roberto Formaggio, and Marlene Aparecida Schiavinato. "Narrow band spectral indexes for chlorophyll determination in soybean canopies [Glycine max (L.) Merril]." Brazilian Journal of Plant Physiology 16, no. 3 (2004): 131–36. http://dx.doi.org/10.1590/s1677-04202004000300002.

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Photosynthetic pigments are essential for plant development. Quantifying these pigments in great extensions of agricultural crops is an important objective in remote sensing for agricultural purposes. This information can be used to produce a more accurate estimation of the physiological state of the vegetation, for species discrimination and productivity estimation. The aim of the present study was to (a) evaluate the potential for estimating chlorophyll content of crop canopies, using narrow band spectral indexes, and (b) in this respect compare the performances of NDVI (a multispectral wide

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Yajima, Daisuke, Teruya Toyoda, Masaaki Kirimura, Kenji Araki, Yasuyuki Ota, and Kensuke Nishioka. "Estimation Model of Agrivoltaic Systems Maximizing for Both Photovoltaic Electricity Generation and Agricultural Production." Energies 16, no. 7 (2023): 3261. http://dx.doi.org/10.3390/en16073261.

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Climate change and increasing food demand are global issues that require immediate attention. The agrivoltaic system, which involves installing solar panels above farmland, can simultaneously solve climate and food issues. However, current systems tend to reduce agricultural production and delay the harvest period due to shading by the solar panels. A delayed harvest period impacts the income of farmers who wish to sell produce at specific times. Incorporating a model that calculates the amount of electricity generated by solar irradiation, this study establishes a model to estimate the correc

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Wang, Mo, Jing Wang, Yunpeng Cui, Juan Liu, and Li Chen. "Agricultural Field Boundary Delineation with Satellite Image Segmentation for High-Resolution Crop Mapping: A Case Study of Rice Paddy." Agronomy 12, no. 10 (2022): 2342. http://dx.doi.org/10.3390/agronomy12102342.

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Parcel-level cropland maps are an essential data source for crop yield estimation, precision agriculture, and many other agronomy applications. Here, we proposed a rice field mapping approach that combines agricultural field boundary extraction with fine-resolution satellite images and pixel-wise cropland classification with Sentinel-1 time series SAR (Synthetic Aperture Radar) imagery. The agricultural field boundaries were delineated by image segmentation using U-net-based fully convolutional network (FCN) models. Meanwhile, a simple decision-tree classifier was developed based on rice pheno

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Williams, Forrest, Brian Gelder, DeAnn Presley, Bryce Pape, and Andrea Einck. "Estimation of Crop Residue Cover Utilizing Multiple Ground Truth Survey Techniques and Multi-Satellite Regression Models." Remote Sensing 16, no. 22 (2024): 4185. http://dx.doi.org/10.3390/rs16224185.

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Soil erosion within agricultural landscapes has significant environmental and economic impacts and is strongly driven by reduced residue cover in agricultural fields. Large-area soil erosion models such as the Daily Erosion Project are important tools for understanding the patterns of soil erosion, but they rely on the accurate estimation of crop residue cover over large regions to infer the tillage practices, an erosion model input. Remote sensing analyses are becoming accepted as a reliable way to estimate crop residue cover, but most use localized training datasets that may not scale well o

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Rabiei, Saman, Ebrahim Babaeian, and Sabine Grunwald. "Surface and Subsurface Soil Moisture Estimation Using Fusion of SMAP, NLDAS-2, and SOLUS100 Data with Deep Learning." Remote Sensing 17, no. 4 (2025): 659. https://doi.org/10.3390/rs17040659.

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Accurate knowledge of surface and subsurface soil moisture (SM) is essential for hydrologic modeling, weather forecasting, and agricultural water management. NASA’s Soil Moisture Active Passive (SMAP) satellite (level 3) provides ‘surface’ SM with 2–3 days temporal resolution, hence lacks daily and subsurface SM information. This study developed a convolutional neural network–long short-term memory (ConvLSTM) deep learning model to produce ‘daily’ surface (5 cm) and subsurface (25 cm) SM products (9 km) by integrating SMAP level 3 ancillary data, North American Land Data Assimilation System (N

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Góral, Justyna, and Włodzimierz Rembisz. "Marże marketingowe i wartości dodane w łańcuchu dostaw żywności w Polsce." Zeszyty Naukowe SGGW w Warszawie - Problemy Rolnictwa Światowego 19(34), no. 4 (2019): 47–57. http://dx.doi.org/10.22630/prs.2019.19.4.55.

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The issue of agricultural producer participation in the final food price is of interest to scientists and politicians. The European Commission (2014, 2016) commissioned the preparation of expertise in this area, as a result of which actions were taken to strengthen the agricultural sector. In Poland, for example, the promotion of direct sales has been intensified. These activities are aimed at shortening the food supply chain and improving the market power of agricultural producers. Market power means the ability of an enterprise to increase the price of its own product without reducing the le

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Cooter, E. J., J. O. Bash, V. Benson, and L. Ran. "Linking agricultural crop management and air quality models for regional to national-scale nitrogen assessments." Biogeosciences Discussions 9, no. 5 (2012): 6095–127. http://dx.doi.org/10.5194/bgd-9-6095-2012.

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Abstract. While nitrogen (N) is an essential element for life, human population growth and demands for energy, transportation and food can lead to excess nitrogen in the environment. A modeling framework is described and implemented, to promote a more integrated, process-based and system-level approach to the estimation of ammonia (NH3) emissions resulting from the application of inorganic nitrogen fertilizers to agricultural soils in the United States. The United States Department of Agriculture (USDA) Environmental Policy Integrated Climate (EPIC) model is used to simulate plant demand-drive

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Cooter, E. J., J. O. Bash, V. Benson, and L. Ran. "Linking agricultural crop management and air quality models for regional to national-scale nitrogen assessments." Biogeosciences 9, no. 10 (2012): 4023–35. http://dx.doi.org/10.5194/bg-9-4023-2012.

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Abstract. While nitrogen (N) is an essential element for life, human population growth and demands for energy, transportation and food can lead to excess nitrogen in the environment. A modeling framework is described and implemented to promote a more integrated, process-based and system-level approach to the estimation of ammonia (NH3) emissions which result from the application of inorganic nitrogen fertilizers to agricultural soils in the United States. The United States Department of Agriculture (USDA) Environmental Policy Integrated Climate (EPIC) model is used to simulate plant demand-dri

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Brandić, Ivan, Alan Antonović, Lato Pezo, et al. "Energy Potentials of Agricultural Biomass and the Possibility of Modelling Using RFR and SVM Models." Energies 16, no. 2 (2023): 690. http://dx.doi.org/10.3390/en16020690.

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Agricultural biomass is one of the most important renewable energy sources. As a byproduct of corn, soybean and sunflower production, large amounts of biomass are produced that can be used as an energy source through conversion. In order to assess the quality and the possibility of the use of biomass, its composition and calorific value must be determined. The use of nonlinear models allows for an easier estimation of the energy properties of biomass concerning certain input and output parameters. In this paper, RFR (Random Forest Regression) and SVM (Support Vector Machine) models were develo

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Bera, Swagota, Arti Shrivastava, Himani Agrawal, and Sunandal Mandal. "A Review on Estimation of soil Macronutrients using Satellite Image Processing." Journal of Physics: Conference Series 2576, no. 1 (2023): 012003. http://dx.doi.org/10.1088/1742-6596/2576/1/012003.

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Abstract Major portion of Indian economy depends on agriculture. More than 40 % of the Indian land is used for agriculture which contributes to Gross Domestic Product (GDP) of the country and also provides employ to the population of the country. Increment in the population day by day increases the requirement for the increment in the yield of the agricultural products. There are several factors which is responsible to control the agricultural product yield. Among them Nitrogen, Phosphorus and Potassium are the macronutrients are the vital elements of the soil . Due to the instability in the c

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Patwary, Md Sazzad Hossain, Md Shahidul Islam, and Rana Al Mosharrafa. "Effect of bank credit on agricultural gross domestic product." Agricultural and Resource Economics: International Scientific E-Journal 9, no. 1 (2023): 188–204. http://dx.doi.org/10.51599/are.2023.09.01.09.

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Purpose. This study aimed to provide the central bank of Bangladesh with some empirical data on the impact of bank agricultural credit on agricultural output as a priority sector lending.  Methodology / approach. Econometric analysis is applied to discover the nature of the relationship between banks’ agricultural credit and agricultural gross domestic product (GDP) and to find the impact of bank agricultural credit on agricultural output in Bangladesh. Data are extracted from secondary sources, i.e., Bangladesh Bank, Bangladesh Bureau of Statistics, World Bank, and Ministry of Finance f

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Kwaw-Nimeson, Enoch, and Ze Tian. "The impact of agricultural producer price on sustainable food security in Africa – a system GMM approach." Agricultural and Resource Economics: International Scientific E-Journal 7, no. 3 (2021): 60–76. http://dx.doi.org/10.51599/are.2021.07.03.04.

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Purpose. Given the efforts towards achieving the United Nations’ Sustainable Development Goals (SDGs) for food security by 2030, this study investigates the moderating impact of public investments in agriculture on the agricultural producer price – agricultural sustainability nexus in 40 African countries covering the period from 2000 till 2019. Methodology / approach. In this study we used multiple regression techniques to explore a dynamic panel data model based on the one-step system Generalized Method of Moments (System-GMM). Proposed by Arellano and Bover and further developed by Bl

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Sudha, Mohan Kumar, Maharana Manorama, and Tarigoppula Aditi. "Smart Agricultural Decision Support Systems for Predicting Soil Nutrition Value Using IoT and Ridge Regression." Agris on-line Papers in Economics and Informatics 14, no. 1 (2022): 95–106. http://dx.doi.org/10.7160/aol.2022.140108.

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Cost effective agricultural crop productivity is an everlasting demand, this predominant expedition has raised a global shift towards practicing smart agricultural methods to increase the productivity and the efficiency of the agricultural sector, using IoT. This research identified the benefits and the challenges in IoT adoption as an alternate for out-of-date agricultural practices. The proposed decision support system using IoT for Smart Soil Nutrition Prediction (SSNP) adopts IR sensors and implements diffuse reflectance infrared spectroscopy. Information is transferred using Arduino and Z

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Singh, Rajesh, and Shobh Nath Tiwari. "Improved Estimator for Population Mean Utilizing Known Medians of Two Auxiliary Variables under Neutrosophic Framework." Neutrosophic Systems with Applications 25 (January 4, 2025): 38–52. https://doi.org/10.61356/j.nswa.2025.25443.

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In the context of classical statistics, the estimation of the population mean is done with determinate, precise, and crisp data when auxiliary information is available. However, there are instances where dealing with uncertain, indeterminate, and imprecise data in interval form is required. To overcome this issue, Florentin Smarandache introduced neutrosophic statistics as a novel approach. This paper introduces a neutrosophic modified ratio-cum-product log-type estimator for the estimation of the population mean using known medians of two auxiliary variables in the neutrosophic context. The b

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Rueda-Ayala, Victor, José Peña, Mats Höglind, José Bengochea-Guevara, and Dionisio Andújar. "Comparing UAV-Based Technologies and RGB-D Reconstruction Methods for Plant Height and Biomass Monitoring on Grass Ley." Sensors 19, no. 3 (2019): 535. http://dx.doi.org/10.3390/s19030535.

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Pastures are botanically diverse and difficult to characterize. Digital modeling of pasture biomass and quality by non-destructive methods can provide highly valuable support for decision-making. This study aimed to evaluate aerial and on-ground methods to characterize grass ley fields, estimating plant height, biomass and volume, using digital grass models. Two fields were sampled, one timothy-dominant and the other ryegrass-dominant. Both sensing systems allowed estimation of biomass, volume and plant height, which were compared with ground truth, also taking into consideration basic economi

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Liefert, William M., David J. Sedik, Robert B. Koopman, Eugenia Serova, and Olga Melyukhina. "Producer Subsidy Equivalents for Russian Agriculture: Estimation and Interpretation." American Journal of Agricultural Economics 78, no. 3 (1996): 792–98. http://dx.doi.org/10.2307/1243306.

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Zhou, Hongkui, Guangpo Geng, Jianhua Yang, Hao Hu, Li Sheng, and Weidong Lou. "Improving Soil Moisture Estimation via Assimilation of Remote Sensing Product into the DSSAT Crop Model and Its Effect on Agricultural Drought Monitoring." Remote Sensing 14, no. 13 (2022): 3187. http://dx.doi.org/10.3390/rs14133187.

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Accurate knowledge of soil moisture is crucial for agricultural drought monitoring. Data assimilation has proven to be a promising technique for improving soil moisture estimation, and various studies have been conducted on soil moisture data assimilation based on land surface models. However, crop growth models, which are ideal tools for agricultural simulation applications, are rarely used for soil moisture assimilation. Moreover, the role of data assimilation in agricultural drought monitoring is seldom investigated. In the present work, we assimilated the European Space Agency (ESA) Climat

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García-Suárez, Federico, Gabriela Pérez-Quesada, and Carlos Molina Riccetto. "Rangeland cattle production in Uruguay: Single-output versus multi-output efficiency measures." Economía Agraria y Recursos Naturales 22, no. 1 (2022): 69–88. http://dx.doi.org/10.7201/earn.2022.01.04.

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Rangeland cattle production is the largest agricultural sector of Uruguay. Ranches produce up to three products (beef, sheep-meat, and wool) usually combined into an equivalent meat (EM) index. The objective is to compare the empirical results from the estimation of a single output stochastic production frontier (SPF) and a multi-output stochastic ray frontier (SRF) to provide insights on the useof the EM index to evaluate ranches performance. Results show similar efficiency scores. The average level of TE is 0.769 for the SPF and 0.779 for the SRF. We cannot discard EM index as a simple measu

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Win, Shelly, Win Win Zin, and Akiyuki Kawasaki. "Development of Flood Damage Estimation Model for Agriculture – Case Study in the Bago Floodplain, Myanmar." Journal of Disaster Research 15, no. 3 (2020): 242–55. http://dx.doi.org/10.20965/jdr.2020.p0242.

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This paper introduces an integrated model that combines the Rainfall Runoff Inundation (RRI) and spatially distributed flood damage estimation models. There are three steps for fulfilling this purpose. The first step is the accomplishment of RRI model for the floodplain region. The second step is a questionnaire survey to analyze the economic damage to affected population and properties caused by the past flooding events; this step aims to estimate the different levels of agricultural damage cost. Finally, the economic flood damage estimation model was developed for the agricultural areas by u

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Jeong, Hanseok, Rabin Bhattarai, Syewoon Hwang, Jae-Gwon Son, and Taeil Jang. "How Ångström–Prescott Coefficients Alter the Estimation of Agricultural Water Demand in South Korea." Water 10, no. 12 (2018): 1851. http://dx.doi.org/10.3390/w10121851.

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The Food and Agriculture Organization (FAO) Penman–Monteith equation, recognized as the standard method for the estimation of reference crop evapotranspiration (ET0), requires many meteorological inputs. The Ångström–Prescott (A-P) formula containing parameters (i.e., a and b) is recommended to determine global solar radiation, one of the essential meteorological inputs, but may result in a considerable difference in ET0 estimation. This study explored the effects of A-P coefficients not only on the estimation of ET0, but also on the irrigation water requirement (IWR) and design water requirem

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Ni, Chunrong, and Katarzyna Dohn. "Research on Optimization of Agricultural Products Cold Chain Logistics Distribution System Based on Low Carbon Perspective." International Journal of Information Systems and Supply Chain Management 17, no. 1 (2024): 1–14. http://dx.doi.org/10.4018/ijisscm.338220.

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Based on thindiscussion of the traditional agricultural product distribution model, this article establishes a low-carbon perspective of urban agricultural product co-distribution model to reduce the level of agricultural product circulation and reduce the impact of distribution activities on the environment. By comprehensively considering the factors affecting carbon emissions in the vehicle delivery process, the fuel consumption and carbon emissions estimation models of delivery vehicles are analyzed and put forward. A mathematical model for the optimization of urban agricultural product col

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Xie, Qinghua, Jinfei Wang, Juan Lopez-Sanchez, et al. "Crop Height Estimation of Corn from Multi-Year RADARSAT-2 Polarimetric Observables Using Machine Learning." Remote Sensing 13, no. 3 (2021): 392. http://dx.doi.org/10.3390/rs13030392.

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This study presents a demonstration of the applicability of machine learning techniques for the retrieval of crop height in corn fields using space-borne PolSAR (Polarimetric Synthetic Aperture Radar) data. Multi-year RADARSAT-2 C-band data acquired over agricultural areas in Canada, covering the whole corn growing period, are exploited. Two popular machine learning regression methods, i.e., Random Forest Regression (RFR) and Support Vector Regression (SVR) are adopted and evaluated. A set of 27 representative polarimetric parameters are extracted from the PolSAR data and used as input feature

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Singh, Nandini, Deeksha Gupta, Mansi Joshi, et al. "Application of Drones Technology in Agriculture: A Modern Approach." Journal of Scientific Research and Reports 30, no. 7 (2024): 142–52. http://dx.doi.org/10.9734/jsrr/2024/v30i72131.

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Drone technology can be used for many applications for agricultural uses, including crop health monitoring and farm operations like weed management, Evapotranspiration estimation, spraying etc. For agricultural applications, regularized smart-farming solutions are being considered, including the use of unmanned aerial vehicles (UAVs). The agricultural UAVs are highly capable, and their use has expanded across all areas of agriculture, including pesticide and fertilizer spraying, seed sowing, and growth assessment and mapping. Accordingly, the market for agricultural UAVs is expected to continu

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